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Optimization of neural network architecture using genetic programming improves detection and modeling of gene-gene interactions in studies of human diseases.

Authors
Type
Published Article
Journal
BMC Bioinformatics
1471-2105
Publisher
Springer (Biomed Central Ltd.)
Publication Date
Volume
4
Pages
28–28
Identifiers
PMID: 12846935
Source
Medline
License
Unknown

Abstract

This study suggests that a machine learning strategy for optimizing neural network architecture may be preferable to traditional trial-and-error approaches for the identification and characterization of gene-gene interactions in common, complex human diseases.

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